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Cy-CNN: cylinder convolution based rotation-invariant neural network for point cloud registration
Point cloud registration is a challenging problem in the condition of large initial misalignments and noises. A major problem encountered in the...
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Single Image Dehazing Using Hybrid Convolution Neural Network
Due to the dispersion of atmospheric particles, the quality of the image becomes inferior. The quality of the frames captured in poor weather...
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Coffee Leaf Disease Classification by Using a Hybrid Deep Convolution Neural Network
The most common symptoms of coffee leaf disease are coffee leaf rust, black rot diseases, and brown eye spot. Leaf rust is the first symptom of...
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Network intrusion detection based on variational quantum convolution neural network
With the rapid development of quantum machine learning (QML), quantum convolutional neural networks (QCNN) have been proposed and shown advantages in...
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Detection of Lung Cancer Using Convolution Neural Network
In the modern world, one of the most prevalent and hazardous cancers is the lung cancer disease that causes the most fatalities each year. Accurate...
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A Novel Ensemble-Learning-Based Convolution Neural Network for Handling Imbalanced Data
Deep-learning-based fault diagnosis of wind turbine has played a significant role in advancing the renewable energy industry. However, the imbalanced...
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Graph Neural Network-Based Short‑Term Load Forecasting with Temporal Convolution
An accurate short-term load forecasting plays an important role in modern power system’s operation and economic development. However, short-term load...
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Analysis of CNN models in classifying Alzheimer's stages: comparison and explainability examination of the proposed separable convolution-based neural network and transfer learning models
Dementia is a condition that affects brain functions and usually occurs with age, resulting in a decrease in cognitive functions (such as thinking,...
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Performance-oriented FPGA-based convolution neural network designs
Convolutional neural network (CNN) is the most well-known algorithm that it has been widely utilized in the applications of the image recognition and...
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Efficient fused convolution neural network (EFCNN) for feature level fusion of medical images
This paper proposes an Efficient Fused Convolution Neural Network (EFCNN) for feature-level fusion of medical images. The proposed network...
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Enhanced convolution neural network and improved SVM to detect and classify diabetic retinopathy
Blood vessels in the retina become damaged as a result of diabetes. If it is not treated early, then it leads to Diabetic retinopathy (DR), which is...
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Sle-CNN: a novel convolutional neural network for sleep stage classification
Many classical methods have been used in automatic sleep stage classification but few methods explore deep learning. Meanwhile, most deep learning...
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A novel multiplier-less convolution core for YOLO CNN ASIC implementation
The You Only Look Once (YOLO) algorithm has a good trade-off between accuracy and execution speed in object detection. The main bottleneck of...
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Novel accelerated methods for convolution neural network with matrix core
The powerful parallel computing capability of GPU and the development of matrix processing unit in recent years provide more possibilities to improve...
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Modified Deep-Convolution Neural Network Model for Flower Images Segmentation and Predictions
Nowadays, recognition of plant, leaf, and flower images is one of the most challenging issues due to the wide variety of classes on earth, which are...
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DSC-Ghost-Conv: A compact convolution module for building efficient neural network architectures
Convolutional Neural Networks (CNNs) have achieved remarkable results in many application fields. However, these CNNs have a large number of network...
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Whole image average pooling-based convolution neural network approach for brain tumour classification
The convolutional neural network has been proven to be a robust recognition and diagnosis model for modelling diseases. In general, a convolutional...
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Sentiment analysis in social internet of things using contextual representations and dilated convolution neural network
The methodologies based on neural networks are substantial to accomplish sentiment analysis in the Social Internet of Things (SIoT). With social...
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Convolutional neural network (CNN) and federated learning-based privacy preserving approach for skin disease classification
This research displays inspect a study on the classification of human skin diseases using medical imaging, with a focus on data privacy preservation....
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HCT-net: hybrid CNN-transformer model based on a neural architecture search network for medical image segmentation
Considering that many manually designed convolutional neural networks (CNNs) for different tasks that require considerable time, labor, and domain...
